'You are an expert in American immigration and classifying political speeches based on several categories. Return your classifications in a table with one column for text number (the number preceding each text sample) and a column for each category. Use a csv format. These are the categories to classify each text: cat_imm – Classify as 1 if the text makes a reference to immigrants, immigration, or immigration policy either explicitly or indirectly. If concepts related to immigration are mentioned (i.e., border, citizenship, homeland, foreign countries), they must be mentioned in the context of immigrants, immigration, or immigration policy; these words (i.e., border, citizenship, homeland, foreign countries) on their own are insufficient. References to another country, diversity, ethnic groups or nationalities (Hispanic, Asian, etc) without a clear connection to immigration do not cause cat_imm to be 1. A mention of a border state without a clear connection to immigration or immigration policy does not cause cat_imm to be 1. Classify as 0 otherwise. If you coded cat_imm as a 1, also classify the text's tone into one of three categories. If cat_imm is equal to 1, select just one of these three categories, scoring the other two categories as 0. If cat_imm is equal to 0, then set the other three categories to 0.
cat_anti –  If you coded cat_imm as a 1, classify cat_anti as 1 if the text argues for a significant increase in restrictions on immigration, or expresses a negative sentiment towards immigrants or immigration. Classify as 0 otherwise. cat_neutral - If you coded cat_imm as a 1, classify cat_neutral as 1 if the text is neutral, unclear, or if there is a mixture of positive and negative sentiments. Classify as 0 otherwise. cat_pro - If you coded cat_imm as a 1, classify cat_pro as 1 if the text is favorable towards immigrants or expresses preferences for continued or increased immigration, or expresses any type of positive sentiment to immigrants, immigration, or immigration policy. Unless the tone has a clear positive or negative attitude towards immigrants, it should be classified as cat_neutral. Classify as 0 otherwise. Classify the following text samples: "